ICLR Papers
6,124 papers found • Page 109 of 123
PhyloGFN: Phylogenetic inference with generative flow networks
MING YANG ZHOU, Zichao Yan, Elliot Layne et al.
Physics-Regulated Deep Reinforcement Learning: Invariant Embeddings
Hongpeng Cao, Yanbing Mao, Lui Sha et al.
Piecewise Linear Parametrization of Policies: Towards Interpretable Deep Reinforcement Learning
Maxime Wabartha, Joelle Pineau
PILOT: An $\mathcal{O}(1/K)$-Convergent Approach for Policy Evaluation with Nonlinear Function Approximation
Zhuqing Liu, Xin Zhang, Jia Liu et al.
PINNACLE: PINN Adaptive ColLocation and Experimental points selection
Gregory Kang Ruey Lau, Apivich Hemachandra, See-Kiong Ng et al.
PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks
Zhiyuan Zhao, Xueying Ding, B. Aditya Prakash
PixArt-$\alpha$: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis
Junsong Chen, Jincheng YU, Chongjian GE et al.
Plan-Seq-Learn: Language Model Guided RL for Solving Long Horizon Robotics Tasks
Murtaza Dalal, Tarun Chiruvolu, Devendra Chaplot et al.
PlaSma: Procedural Knowledge Models for Language-based Planning and Re-Planning
Faeze Brahman, Chandra Bhagavatula, Valentina Pyatkin et al.
Plug-and-Play: An Efficient Post-training Pruning Method for Large Language Models
Yingtao Zhang, Haoli Bai, Haokun Lin et al.
Plug-and-Play Policy Planner for Large Language Model Powered Dialogue Agents
Yang Deng, Wenxuan Zhang, Wai Lam et al.
Plug-and-Play Posterior Sampling under Mismatched Measurement and Prior Models
Marien Renaud, Jiaming Liu, Valentin De Bortoli et al.
Plugin estimators for selective classification with out-of-distribution detection
Harikrishna Narasimhan, Aditya Krishna Menon, Wittawat Jitkrittum et al.
PnP Inversion: Boosting Diffusion-based Editing with 3 Lines of Code
Xuan Ju, Ailing Zeng, Yuxuan Bian et al.
Point2SSM: Learning Morphological Variations of Anatomies from Point Clouds
Jadie Adams, Shireen Elhabian
Poisoned Forgery Face: Towards Backdoor Attacks on Face Forgery Detection
Jiawei Liang, Siyuan Liang, Aishan Liu et al.
Policy Rehearsing: Training Generalizable Policies for Reinforcement Learning
Chengxing Jia, Chen-Xiao Gao, Hao Yin et al.
PolyGCL: GRAPH CONTRASTIVE LEARNING via Learnable Spectral Polynomial Filters
Jingyu Chen, Runlin Lei, Zhewei Wei
Polynomial Width is Sufficient for Set Representation with High-dimensional Features
Peihao Wang, Shenghao Yang, Shu Li et al.
Polynormer: Polynomial-Expressive Graph Transformer in Linear Time
Chenhui Deng, Zichao Yue, Zhiru Zhang
Poly-View Contrastive Learning
Amitis Shidani, R Devon Hjelm, Jason Ramapuram et al.
PolyVoice: Language Models for Speech to Speech Translation
Qianqian Dong, Zhiying Huang, Qiao Tian et al.
Pooling Image Datasets with Multiple Covariate Shift and Imbalance
Sotirios Panagiotis Chytas, Vishnu Lokhande, Vikas Singh
PORF: POSE RESIDUAL FIELD FOR ACCURATE NEURAL SURFACE RECONSTRUCTION
Jia-Wang Bian, Wenjing Bian, Victor Prisacariu et al.
PoSE: Efficient Context Window Extension of LLMs via Positional Skip-wise Training
Dawei Zhu, Nan Yang, Liang Wang et al.
Pose Modulated Avatars from Video
Chunjin Song, Bastian Wandt, Helge Rhodin
Posterior Sampling Based on Gradient Flows of the MMD with Negative Distance Kernel
Paul Hagemann, Johannes Hertrich, Fabian Altekrüger et al.
Post-hoc bias scoring is optimal for fair classification
Wenlong Chen, Yegor Klochkov, Yang Liu
Predicting Emergent Abilities with Infinite Resolution Evaluation
Shengding Hu, Xin Liu, Xu Han et al.
Prediction Error-based Classification for Class-Incremental Learning
Michał Zając, Tinne Tuytelaars, Gido M van de Ven
Prediction without Preclusion: Recourse Verification with Reachable Sets
Avni Kothari, Bogdan Kulynych, Tsui-Wei Weng et al.
Predictive auxiliary objectives in deep RL mimic learning in the brain
Ching Fang, Kimberly Stachenfeld
Predictive, scalable and interpretable knowledge tracing on structured domains
Hanqi Zhou, Robert Bamler, Charley Wu et al.
PRES: Toward Scalable Memory-Based Dynamic Graph Neural Networks
Junwei Su, Difan Zou, Chuan Wu
Pre-Training and Fine-Tuning Generative Flow Networks
Ling Pan, Moksh Jain, Kanika Madan et al.
Pre-Training Goal-based Models for Sample-Efficient Reinforcement Learning
Haoqi Yuan, Zhancun Mu, Feiyang Xie et al.
Pre-training LiDAR-based 3D Object Detectors through Colorization
Tai-Yu Pan, Chenyang Ma, Tianle Chen et al.
Pre-training Sequence, Structure, and Surface Features for Comprehensive Protein Representation Learning
Youhan Lee, Hasun Yu, Jaemyung Lee et al.
Pre-training with Random Orthogonal Projection Image Modeling
Maryam Haghighat, Peyman Moghadam, Shaheer Mohamed et al.
Pre-training with Synthetic Data Helps Offline Reinforcement Learning
Zecheng Wang, Che Wang, Zixuan Dong et al.
PRIME: Prioritizing Interpretability in Failure Mode Extraction
Keivan Rezaei, Mehrdad Saberi, Mazda Moayeri et al.
Principled Architecture-aware Scaling of Hyperparameters
Wuyang Chen, Junru Wu, Zhangyang Wang et al.
Principled Federated Domain Adaptation: Gradient Projection and Auto-Weighting
Enyi Jiang, Yibo Jacky Zhang, Sanmi Koyejo
Prioritized Soft Q-Decomposition for Lexicographic Reinforcement Learning
Finn Rietz, Erik Schaffernicht, Stefan Heinrich et al.
Privacy Amplification for Matrix Mechanisms
Christopher Choquette-Choo, Arun Ganesh, Thomas Steinke et al.
Privacy-Preserving In-Context Learning for Large Language Models
Tong Wu, Ashwinee Panda, Jiachen (Tianhao) Wang et al.
Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation
Xinyu Tang, Richard Shin, Huseyin Inan et al.
Privately Aligning Language Models with Reinforcement Learning
Fan Wu, Huseyin Inan, Arturs Backurs et al.
Private Zeroth-Order Nonsmooth Nonconvex Optimization
Qinzi Zhang, Hoang Tran, Ashok Cutkosky
Privileged Sensing Scaffolds Reinforcement Learning
Edward Hu, James Springer, Oleh Rybkin et al.